Source code for jax._src.scipy.stats.multinomial

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import scipy.stats as osp_stats
from jax import lax
import jax.numpy as jnp
from jax._src.numpy.util import implements, promote_args_inexact, promote_args_numeric
from jax._src.scipy.special import gammaln, xlogy
from jax._src.typing import Array, ArrayLike


[docs] @implements(osp_stats.multinomial.logpmf, update_doc=False) def logpmf(x: ArrayLike, n: ArrayLike, p: ArrayLike) -> Array: """JAX implementation of scipy.stats.multinomial.logpmf.""" p, = promote_args_inexact("multinomial.logpmf", p) x, n = promote_args_numeric("multinomial.logpmf", x, n) if not jnp.issubdtype(x.dtype, jnp.integer): raise ValueError(f"x and n must be of integer type; got x.dtype={x.dtype}, n.dtype={n.dtype}") x = x.astype(p.dtype) n = n.astype(p.dtype) logprobs = gammaln(n + 1) + jnp.sum(xlogy(x, p) - gammaln(x + 1), axis=-1) return jnp.where(jnp.equal(jnp.sum(x), n), logprobs, -jnp.inf)
[docs] @implements(osp_stats.multinomial.pmf, update_doc=False) def pmf(x: ArrayLike, n: ArrayLike, p: ArrayLike) -> Array: """JAX implementation of scipy.stats.multinomial.pmf.""" return lax.exp(logpmf(x, n, p))